Exposure–response analysis
Exposure–response analysis relates an exposure measure such as AUC or Ctrough to an efficacy or safety endpoint. It is used to justify a dose, but confounding can make the relationship look steeper than it is.
Definition
Exposure–response (E–R) analysis relates a measure of exposure (AUC, Ctrough or Cmax) to a clinical endpoint of efficacy or safety. It is used to judge whether a dose or a dose change would matter, and to support dose selection.
Pitfalls
- Confounding: for antibodies, patients with more severe disease often have higher clearance, so lower exposure and a worse outcome, which makes the relationship look steeper than the causal effect of exposure.
- Flat relationships: when response barely changes across the exposure range, a small change in exposure is unlikely to matter, but the range studied limits this conclusion.
- Choice of metric: different metrics (trough or average) can give different conclusions for regimens with different intervals.
On this site
The anti-PD-1 analysis compares exposure only. It notes that the exposure–response relationship of these antibodies has been reported to be flat, and says that whether falling slightly below the lower limit of the range matters clinically is outside what an exposure comparison shows. The sotorasib dose comparison works from arm-level outcomes, and the RAS inhibitor analysis builds target-coverage scenarios from public PK/PD data.
Frequently asked questions
Why can an exposure–response relationship be misleading?
Because exposure and outcome can share a cause, for example disease severity affects both clearance and survival, so the association is not the effect of changing the dose.
Does a flat exposure–response relationship mean the dose does not matter?
Only within the range of exposures studied; outside that range, or for safety, the relationship may not be flat.